Synopses & Reviews
Authors Ward Cheney and David Kincaid show students of science and engineering the potential computers have for solving numerical problems and give them ample opportunities to hone their skills in programming and problem solving. The text also helps students learn about errors that inevitably accompany scientific computations and arms them with methods for detecting, predicting, and controlling these errors. A more theoretical text with a different menu of topics is the authors' highly regarded NUMERICAL ANALYSIS: MATHEMATICS OF SCIENTIFIC COMPUTING, THIRD EDITION.
Review
"This is one of the best textbooks on elementary numerical analysis available today. The instructor can easily tailor the abundant material it offers for any particular course need. Another bright spot of this book is its myriad selections of excellently compiled exercise problems that go very well with the main text."
Review
"This is a well written text full of excellent examples."
Synopsis
Authors Ward Cheney and David Kincaid show enthusiasts of science and engineering the potential computers have for solving numerical problems and give them ample opportunities to hone their skills in programming and problem solving. The book also helps readers learn about errors that inevitably accompany scientific computations and arms them with methods for detecting, predicting, and controlling these errors.
Description
Includes bibliographical references (p. 653-660) and index.
About the Author
Ward Cheney is Professor of Mathematics at the University of Texas at Austin. His research interests include approximation theory, numerical analysis, and extremum problems.David Kincaid is Senior Lecturer in the Department of Computer Sciences at the University of Texas at Austin. Also, he is the Interim Director of the Center for Numerical Analysis (CNA) within the Institute for Computational Engineering and Sciences (ICES).
Table of Contents
1. INTRODUCTION. Preliminary Remarks. Review of Taylor Series. 2. NUMBER REPRESENTATION AND ERRORS. Representation of Numbers in Different Bases. Floating-Point Representation. Loss of Significance. 3. LOCATING ROOTS OF EQUATIONS. Bisection Method. Newton's Method. Secant Method. 4. INTERPOLATION AND NUMERICAL DIFFERENTIATION. Polynomial Interpolation. Errors in Polynomial Interpolation. Estimating Derivatives and Richardson Extrapolation. 5. NUMERICAL INTEGRATION. Definite Integral. Trapezoid Rule. Romberg Algorithm. 6. MORE ON NUMERICAL INTEGRATION. An Adaptive Simpson's Scheme. Gaussian Quadrature Formulas. 7. SYSTEMS OF LINEAR EQUATIONS. Naive Gaussian Elimination. Gaussian Elimination with Scaled Partial Pivoting. Tridiagonal and Banded Systems. 8. MORE ON SYSTEMS OF LINEAR EQUATIONS. Factorizations. Iterative Solution of Linear Systems. Eigenvalues and Eigenvectors. Power Methods. 9. APPROXIMATION BY SPLINE FUNCTIONS. First-Degree and Second-Degree Splines. Natural Cubic Splines. B splines: Interpolation and Approximation by B Splines. 10. ORDINARY DIFFERENTIAL EQUATIONS. Initial-Value Problem: Analytical vs. Numerical Solution. Taylor Series Methods. Runge-Kutta Methods. Stability and Adaptive Runge-Kutta and Multi-Step Methods. 11. SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS. Methods for First-Order Systems. Higher-Order Equations and Systems. Adams-Moulton Methods. 12. SMOOTHING OF DATA AND THE METHOD OF LEAST SQUARES. The Method of Least Squares. Orthogonal Systems and Chebyshev Polynomials. Other Examples of the Least-Squares Principle. 13. MONTE CARLO METHODS AND SIMULATION. Random Numbers. Estimation of Areas and Volumes by\hfill\break Monte Carlo Techniques. Simulation. 14. BOUNDARY VALUE PROBLEMS FOR ORDINARY DIFFERENTIAL EQUATIONS. Shooting Method. A Discretization Method. 15. PARTIAL DIFFERENTIAL EQUATIONS. Some Partial Differential Equations from Applied Problems. Parabolic Problems. Hyperbolic Problems. Elliptic Problems. 16. MINIMIZATION OF MULTIVARIATE FUNCTIONS. One-Variable Case. Multivariate Case. 17. LINEAR PROGRAMMING. Standard Forms and Duality. Simplex Method. Approximate Solution ofInconsistent Linear Systems. Appendices. Advice on Good Programming Practices. An Overview of Mathematical Software on the Web. Additional Details on IEEE Floating-Point Arithmetic. Linear Algebra Concepts and Notation. Sir Isaac Newton: Never at Rest. Answers for Selected Problems. Bibliography.